{"created":"2023-07-25T01:41:30.938454+00:00","id":2000449,"links":{},"metadata":{"_buckets":{"deposit":"8f15dccd-9849-4bbb-93f4-4c8b61fc12e7"},"_deposit":{"created_by":15,"id":"2000449","owner":"15","owners":[15],"pid":{"revision_id":0,"type":"depid","value":"2000449"},"status":"published"},"_oai":{"id":"oai:kitami-it.repo.nii.ac.jp:02000449","sets":["1:87"]},"author_link":[],"item_1646810750418":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_3_biblio_info_186":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"14","bibliographicPageEnd":"6340","bibliographicPageStart":"6340","bibliographicVolumeNumber":"11","bibliographic_titles":[{"bibliographic_title":"Applied Sciences","bibliographic_titleLang":"en"}]}]},"item_3_description_184":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"In this paper, we present a Deep Learning-based system for the support of information\ntriaging on Twitter during emergency situations, such as disasters, or other influential events, such\nas political elections. The system is based on the assumption that a different type of information\nis required right after the event and some time after the event occurs. In a preliminary study, we\nanalyze the language behavior of Twitter users during two kinds of influential events, namely,\nnatural disasters and political elections. In the study, we analyze the credibility of information\nincluded by users in tweets in the above-mentioned situations, by classifying the information into\ntwo kinds: Primary Information (first-hand reports) and Secondary Information (second-hand reports,\nretweets, etc.). We also perform sentiment analysis of the data to check user attitudes toward the\noccurring events. Next, we present the structure of the system and compare a number of classifiers,\nincluding the proposed one based on Convolutional Neural Networks. Finally, we validate the\nsystem by performing an in-depth analysis of information obtained after a number of additional\nevents, including an eruption of a Japanese volcano Ontake on 27 September 2014, as well as heavy\nrains and typhoons that occurred in 2020. We confirm that the methods works sufficiently well\neven when trained on data from nearly 10 years ago, which strongly suggests that the model is\nwell-generalized and sufficiently grasps important aspects of each type of classified information.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_3_publisher_212":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"MDPI","subitem_publisher_language":"en"}]},"item_3_relation_191":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doi.org/10.3390/app11146340","subitem_relation_type_select":"DOI"}}]},"item_3_rights_192":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"c2021 by the authors. Licensee MDPI","subitem_rights_language":"en"}]},"item_3_select_195":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_select_item":"publisher","subitem_select_language":"en"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Michal Ptaszynski","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Fumito Masui","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Yuuto Fukushima","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Yuuto Oikawa","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Hiroshi Hayakawa","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Yasunori Miyamori","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Kiyoshi Takahashi","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Shunzo Kawajiri","creatorNameLang":"en"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2023-07-25"}],"filename":"applsci-11-06340-v2.pdf","filesize":[{"value":"4.5 MB"}],"format":"application/pdf","licensetype":"license_0","url":{"url":"https://kitami-it.repo.nii.ac.jp/record/2000449/files/applsci-11-06340-v2.pdf"},"version_id":"26305c2b-3a5c-450a-8bbf-bbd03527177c"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Deep Learning for Information Triage on Twitter","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Deep Learning for Information Triage on Twitter","subitem_title_language":"en"}]},"item_type_id":"3","owner":"15","path":["87"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2023-07-25"},"publish_date":"2023-07-25","publish_status":"0","recid":"2000449","relation_version_is_last":true,"title":["Deep Learning for Information Triage on Twitter"],"weko_creator_id":"15","weko_shared_id":3},"updated":"2024-06-03T02:16:39.463749+00:00"}